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Black 20 release

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This commit is contained in:
Lysandre
2020-08-26 17:20:22 +02:00
parent e78c110338
commit a75c64d80c
191 changed files with 4807 additions and 3503 deletions
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31
tests/test_modeling_tf_common.py
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@@ -155,7 +155,8 @@ class TFModelTesterMixin:
self.assertEqual(len(outputs), num_out)
self.assertEqual(len(hidden_states), self.model_tester.num_hidden_layers + 1)
self.assertListEqual(
list(hidden_states[0].shape[-2:]), [self.model_tester.seq_length, self.model_tester.hidden_size],
list(hidden_states[0].shape[-2:]),
[self.model_tester.seq_length, self.model_tester.hidden_size],
)
@slow
@@ -486,7 +487,8 @@ class TFModelTesterMixin:
hidden_states = [t.numpy() for t in outputs[-1]]
self.assertEqual(len(hidden_states), self.model_tester.num_hidden_layers + 1)
self.assertListEqual(
list(hidden_states[0].shape[-2:]), [self.model_tester.seq_length, self.model_tester.hidden_size],
list(hidden_states[0].shape[-2:]),
[self.model_tester.seq_length, self.model_tester.hidden_size],
)
for model_class in self.all_model_classes:
@@ -591,9 +593,15 @@ class TFModelTesterMixin:
x = wte([input_ids, None, None, None], mode="embedding")
except Exception:
if hasattr(self.model_tester, "embedding_size"):
x = tf.ones(input_ids.shape + [self.model_tester.embedding_size], dtype=tf.dtypes.float32,)
x = tf.ones(
input_ids.shape + [self.model_tester.embedding_size],
dtype=tf.dtypes.float32,
)
else:
x = tf.ones(input_ids.shape + [self.model_tester.hidden_size], dtype=tf.dtypes.float32,)
x = tf.ones(
input_ids.shape + [self.model_tester.hidden_size],
dtype=tf.dtypes.float32,
)
return x
def test_inputs_embeds(self):
@@ -700,7 +708,14 @@ class TFModelTesterMixin:
model.generate(input_ids, do_sample=False, num_return_sequences=3, num_beams=2)
# num_return_sequences > 1, sample
self._check_generated_ids(model.generate(input_ids, do_sample=True, num_beams=2, num_return_sequences=2,))
self._check_generated_ids(
model.generate(
input_ids,
do_sample=True,
num_beams=2,
num_return_sequences=2,
)
)
# num_return_sequences > 1, greedy
self._check_generated_ids(model.generate(input_ids, do_sample=False, num_beams=2, num_return_sequences=2))
@@ -895,7 +910,8 @@ class UtilsFunctionsTest(unittest.TestCase):
)
non_inf_expected_idx = tf.convert_to_tensor(
[[0, 0], [0, 9], [0, 10], [0, 25], [0, 26], [1, 13], [1, 17], [1, 18], [1, 20], [1, 27]], dtype=tf.int32,
[[0, 0], [0, 9], [0, 10], [0, 25], [0, 26], [1, 13], [1, 17], [1, 18], [1, 20], [1, 27]],
dtype=tf.int32,
) # expected non filtered idx as noted above
non_inf_expected_output = tf.convert_to_tensor(
@@ -907,7 +923,8 @@ class UtilsFunctionsTest(unittest.TestCase):
non_inf_output = output[output != -float("inf")]
non_inf_idx = tf.cast(
tf.where(tf.not_equal(output, tf.constant(-float("inf"), dtype=tf.float32))), dtype=tf.int32,
tf.where(tf.not_equal(output, tf.constant(-float("inf"), dtype=tf.float32))),
dtype=tf.int32,
)
tf.debugging.assert_near(non_inf_output, non_inf_expected_output, rtol=1e-12)